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diff --git a/Linear_Algebra_by_K._Hoffman_and_R._Kunze/Chapter5.ipynb b/Linear_Algebra_by_K._Hoffman_and_R._Kunze/Chapter5.ipynb deleted file mode 100755 index 9d29340c..00000000 --- a/Linear_Algebra_by_K._Hoffman_and_R._Kunze/Chapter5.ipynb +++ /dev/null @@ -1,358 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Chapter 5 - Determinants" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 143 Example 5.3" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A = \n", - "[[ 3. 9.]\n", - " [ 3. 1.]]\n", - "D1(A) = 3.0\n", - "D2(A) = -27.0\n", - "D(A) = D1(A) + D2(A) = -24.0\n", - "That is, D is a 2-linear function.\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "A = np.random.rand(2,2)\n", - "for x in range(0,2):\n", - " for y in range(0,2):\n", - " A[x,y]=round(A[x,y]*10)\n", - "print 'A = \\n',A\n", - "\n", - "D1 = A[0,0]*A[1,1]\n", - "D2 = - A[0,1]*A[1,0]\n", - "print 'D1(A) = ',D1\n", - "print 'D2(A) = ',D2\n", - "print 'D(A) = D1(A) + D2(A) = ',D1 + D2\n", - "print 'That is, D is a 2-linear function.'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 145 Example 5.4" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A = \n", - "Matrix([[x, 0, -x**2], [0, 1, 0], [1, 0, x**3]])\n", - "e1,e2,e3 are the rows of 3*3 identity matrix, then\n", - "e1 = [ 1. 0. 0.]\n", - "e2 = [ 0. 1. 0.]\n", - "e3 = [ 0. 0. 1.]\n", - "D(A) = D(x*e1 - x**2*e3, e2, e1 + x**3*e3)\n", - "Since, D is linear as a function of each row,\n", - "D(A) = x*D(e1,e2,e1 + x**3*e3) - x**2*D(e3,e2,e1 + x**3*e3)\n", - "D(A) = x*D(e1,e2,e1) + x**4*D(e1,e2,e3) - x**2*D(e3,e2,e1) - x**5*D(e3,e2,e3)\n", - "As D is alternating, So\n", - "D(A) = (x**4 + x**2)*D(e1,e2,e3)\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import sympy as sp\n", - "\n", - "x = sp.Symbol(\"x\")\n", - "A = sp.Matrix(([x, 0, -x**2],[0, 1, 0],[1, 0, x**3]))\n", - "print 'A = \\n',A\n", - "print 'e1,e2,e3 are the rows of 3*3 identity matrix, then'\n", - "T = np.identity(3)\n", - "e1 = T[0,:]\n", - "e2 = T[1,:]\n", - "e3 = T[2,:]\n", - "print 'e1 = ',e1\n", - "print 'e2 = ',e2\n", - "print 'e3 = ',e3\n", - "print 'D(A) = D(x*e1 - x**2*e3, e2, e1 + x**3*e3)'\n", - "print 'Since, D is linear as a function of each row,'\n", - "print 'D(A) = x*D(e1,e2,e1 + x**3*e3) - x**2*D(e3,e2,e1 + x**3*e3)'\n", - "print 'D(A) = x*D(e1,e2,e1) + x**4*D(e1,e2,e3) - x**2*D(e3,e2,e1) - x**5*D(e3,e2,e3)'\n", - "print 'As D is alternating, So'\n", - "print 'D(A) = (x**4 + x**2)*D(e1,e2,e3)'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 147 Example 5.5" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A = \n", - "Matrix([[x - 1, x**2, x**3], [0, x - 2, 1], [0, 0, x - 3]])\n", - "\n", - "E(A) = x**3 - 6*x**2 + 11*x - 6\n", - "--------------------------------------\n", - "A = \n", - "Matrix([[0, 1, 0], [0, 0, 1], [1, 0, 0]])\n", - "\n", - "E(A) = 1\n" - ] - } - ], - "source": [ - "import sympy as sp\n", - "\n", - "#part a\n", - "x = sp.Symbol('x')\n", - "A = sp.Matrix(([x-1, x**2, x**3],[0, x-2, 1],[0, 0, x-3]))\n", - "print 'A = \\n',A\n", - "print '\\nE(A) = ',A.det()\n", - "print '--------------------------------------'\n", - "#part b\n", - "A = sp.Matrix(([0 ,1, 0],[0, 0, 1],[1 ,0, 0]))\n", - "print 'A = \\n',A\n", - "print '\\nE(A) = ',A.det()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 158 Example 5.6" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Given Matrix:\n", - "A = \n", - "[[ 1 -1 2 3]\n", - " [ 2 2 0 2]\n", - " [ 4 1 -1 -1]\n", - " [ 1 2 3 0]]\n", - "After, Subtracting muliples of row 1 from rows 2 3 4\n", - "R2 = R2 - 2*R1\n", - "R3 = R3 - 4*R1\n", - "R4 = R4 - R1\n", - "A = \n", - "[[ 1 -1 2 3]\n", - " [ 0 4 -4 -4]\n", - " [ 0 5 -9 -13]\n", - " [ 0 3 1 -3]]\n", - "We obtain the same determinant as before.\n", - "Now, applying some more row transformations as:\n", - "R3 = R3 - 5/4 * R2\n", - "R4 = R4 - 3/4 * R2\n", - "We get B as:\n", - "B = \n", - "[[ 1 -1 2 3]\n", - " [ 0 4 -4 -4]\n", - " [ 0 0 -4 -8]\n", - " [ 0 0 4 0]]\n", - "Now,determinant of A and B will be same\n", - "det A = det B = 128.0\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "print 'Given Matrix:'\n", - "A = np.array([[1, -1, 2, 3],[ 2, 2, 0, 2],[ 4, 1 ,-1, -1],[1, 2, 3, 0]])\n", - "print 'A = \\n',A\n", - "print 'After, Subtracting muliples of row 1 from rows 2 3 4'\n", - "print 'R2 = R2 - 2*R1'\n", - "A[1,:] = A[1,:] - 2 * A[0,:]\n", - "print 'R3 = R3 - 4*R1'\n", - "A[2,:] = A[2,:] - 4 * A[0,:]\n", - "print 'R4 = R4 - R1'\n", - "A[3,:] = A[3,:] - A[0,:]\n", - "print 'A = \\n',A\n", - "T = A# #Temporary matrix to store A\n", - "print 'We obtain the same determinant as before.'\n", - "print 'Now, applying some more row transformations as:'\n", - "print 'R3 = R3 - 5/4 * R2'\n", - "T[2,:] = T[2,:] - 5./4 * T[1,:]\n", - "print 'R4 = R4 - 3/4 * R2'\n", - "T[3,:] = T[3,:] - 3./4 * T[1,:]\n", - "B = T#\n", - "print 'We get B as:'\n", - "print 'B = \\n',B\n", - "print 'Now,determinant of A and B will be same'\n", - "print 'det A = det B = ',np.linalg.det(B)\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 160 Example 5.7" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A = \n", - "Matrix([[x**2 + x, x + 1], [x - 1, 1]])\n", - "B = \n", - "Matrix([[x**2 - 1, x + 2], [x**2 - 2*x + 3, x]])\n", - "det A = x + 1\n", - "det B = -6\n", - "Thus, A is not invertible over K whereas B is invertible\n", - "adj A = Matrix([[(x + 1)*((x - 1)/(x*(x + 1)) + 1/(x*(x + 1))), -x - 1], [-x + 1, x*(x + 1)]])\n", - "adj B = Matrix([[-6*(x + 2)*(-x**2/6 + 1/6)*(x**2 - 2*x + 3)/(x**2 - 1)**2 - 6/(x**2 - 1), 6*(x + 2)*(-x**2/6 + 1/6)/(x**2 - 1)], [6*(-x**2/6 + 1/6)*(x**2 - 2*x + 3)/(x**2 - 1), x**2 - 1]])\n", - "(adj A)A = (x+1)I\n", - "(adj B)B = -6I\n", - "B inverse = Matrix([[(x + 2)*(-x**2/6 + 1/6)*(x**2 - 2*x + 3)/(x**2 - 1)**2 + 1/(x**2 - 1), -(x + 2)*(-x**2/6 + 1/6)/(x**2 - 1)], [-(-x**2/6 + 1/6)*(x**2 - 2*x + 3)/(x**2 - 1), -x**2/6 + 1/6]])\n" - ] - } - ], - "source": [ - "import sympy as sp\n", - "import numpy as np\n", - "\n", - "x = sp.Symbol(\"x\")\n", - "A = sp.Matrix(([x**2+x, x+1],[x-1, 1]))\n", - "B = sp.Matrix(([x**2-1, x+2],[x**2-2*x+3, x]))\n", - "print 'A = \\n',A\n", - "print 'B = \\n',B\n", - "print 'det A = ',A.det()\n", - "print 'det B = ',B.det()\n", - "print 'Thus, A is not invertible over K whereas B is invertible'\n", - "\n", - "print 'adj A = ',(A**-1)*A.det()\n", - "print 'adj B = ',(B**-1)*B.det()\n", - "print '(adj A)A = (x+1)I'\n", - "print '(adj B)B = -6I'\n", - "print 'B inverse = ',B**-1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Page 161 Example 5.8" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A = \n", - "[[1 2]\n", - " [3 4]]\n", - "det A = Determinant of A is: -2.0\n", - "Adjoint of A is: [[-2. -0. ]\n", - " [-0. -0.5]]\n", - "Thus, A is not invertible as a matrix over the ring of integers.\n", - "But, A can be regarded as a matrix over field of rational numbers.\n", - "Then, A is invertible and Inverse of A is: [[-2. 1. ]\n", - " [ 1.5 -0.5]]\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "A = np.array([[1, 2],[3, 4]])\n", - "print 'A = \\n',A\n", - "d = np.linalg.det(A)#\n", - "print 'det A = ','Determinant of A is:',d\n", - "\n", - "\n", - "ad = (d* np.identity(2)) / A\n", - "print 'Adjoint of A is:',ad\n", - "\n", - "\n", - "print 'Thus, A is not invertible as a matrix over the ring of integers.'\n", - "print 'But, A can be regarded as a matrix over field of rational numbers.'\n", - "In = np.linalg.inv(A)#\n", - "#The A inverse matrix given in book has a wrong entry of 1/2. It should be -1/2.\n", - "print 'Then, A is invertible and Inverse of A is:',In\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.9" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} |